Widespread use of digital formats has increased the use of digital audio, such as Motion Picture Experts Group (MPEG) audio, in the multimedia and music industry alike. One method of compressing audio is performed by analyzing audio frames of an audio stream using a psycho-acoustical model to generate a signal-to-mask ratio table that is subsequently used by a compression algorithm to allocate data bits to various frequency bands. Typically, the psycho-acoustical model is implemented in a batch (non-real time) mode. However, with the steady increase in processing capability of data processors, instant real-time updating of the signal-to-mask ratio table has also been used, whereby each frame of the audio stream is analyzed and used to update the SMR table. However, real-time applications require costly high performance processing, such as the use of specialized digital signal processors, to process the audio stream in its entirety. Regardless of the ability to process audio in real-time to implement psycho-acoustical based compression, doing so is a computationally intensive process. Therefore, a system and or method of reducing the processing bandwidth, and hence the cost, used to implement psycho-acoustical audio compression in real-time would be useful.